4 papers
CQC-RAG: Robust Retrieval-Augmented Generation via Cross-Query Consistency
Yanjia Sun, Sifan Liu, Jie Shao
Retrieval-Augmented Generation (RAG) has become a common approach for improving the factuality of Large Language Models (LLMs), yet its reliability remains highly sensitive to how…
Efficient Reinforcement Learning for Large Language Models with Intrinsic Exploration
Yan Sun, Jia Guo, Stanley Kok +3
Reinforcement learning with verifiable rewards (RLVR) has improved the reasoning ability of large language models, yet training remains costly because many rollouts contribute litt…
Talk Less, Verify More: Improving LLM Assistants with Semantic Checks and Execution Feedback
Yan Sun, Ming Cai, Stanley Kok
As large language model (LLM) assistants become increasingly integrated into enterprise workflows, their ability to generate accurate, semantically aligned, and executable outputs…
Investigating the Effects of Cognitive Biases in Prompts on Large Language Model Outputs
Yan Sun, Stanley Kok
This paper investigates the influence of cognitive biases on Large Language Models (LLMs) outputs. Cognitive biases, such as confirmation and availability biases, can distort user…